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SIGPRO
2010
73views more  SIGPRO 2010»
14 years 8 months ago
Continuous-time and continuous-discrete-time unscented Rauch-Tung-Striebel smoothers
This article considers the application of the unscented transformation to approximate fixed-interval optimal smoothing of continuous-time non-linear stochastic systems. The propo...
Simo Särkkä
CDC
2010
IEEE
160views Control Systems» more  CDC 2010»
14 years 5 months ago
Aggregation-based model reduction of a Hidden Markov Model
This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
Kun Deng, Prashant G. Mehta, Sean P. Meyn
GECCO
2007
Springer
235views Optimization» more  GECCO 2007»
15 years 4 months ago
Expensive optimization, uncertain environment: an EA-based solution
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
Maumita Bhattacharya
GIS
2007
ACM
15 years 11 months ago
Dynamics-aware similarity of moving objects trajectories
This work addresses the problem of obtaining the degree of similarity between trajectories of moving objects. Typically, a Moving Objects Database (MOD) contains sequences of (loc...
Goce Trajcevski, Hui Ding, Peter Scheuermann, Robe...
ICML
1996
IEEE
15 years 2 months ago
A Convergent Reinforcement Learning Algorithm in the Continuous Case: The Finite-Element Reinforcement Learning
This paper presents a direct reinforcement learning algorithm, called Finite-Element Reinforcement Learning, in the continuous case, i.e. continuous state-space and time. The eval...
Rémi Munos